Objective
Supporting forest management planning processes with remote sensing techniques – challenges and opportunities

Content
In forestry, long- and mid-term strategical planning and operational harvest planning are common practices in the strategic organization of forest production and utilization. In this context, information about the forest, for example regarding its structure, is required. In light of accelerating climate change and associated frequent biotic and abiotic calamities, such forest structure data are particularly valuable for ensuring sustainable, adaptive, and productive forest management. However, there are considerable deficits regarding the availability of the required data. As a rule, they are not available in high resolution over whole areas and can only be determined approximately and with relatively high effort by forest enterprises within the framework of forest planning.
Using different remote sensing technologies, the required data could be obtained in a cost-effective, timely and accurate manner. Hence, the aim of the project is to develop practical methods that use various remote sensing data to provide reliable information about the forest. The remote sensing data used range from aerial and satellite images to airborne laser scanning (ALS) data. Methodologically, automated and reproducible procedures from the field of machine and deep learning are applied. The latter in particular has gained considerable importance in remote sensing-based analyses in recent years and promises to increase the accuracy of classifications and segmentations.
Finally, it will be assessed to what extent the different remote sensing techniques can be used to support forest management planning and the challenges and opportunities presented by each application.


Appropriation period
02.2022 - 10.2025

Funded by
Federal Ministry of Food and Agriculture (BMEL) through the Agency for Renewable Resources e. V. (FNR) as part of the "Renewable Resources" funding program (funding code: 2220NR102X)

Cooperation partner
Northwest German Forest Research Institute

Project leadership
Dr. Dominik Seidel

Person(s) in charge
Florian Franz

Publications
not available so far